Background2D

class gammapy.irf.Background2D(energy_lo, energy_hi, offset_lo, offset_hi, data, meta=None, interp_kwargs=None)

Bases: object

Background 2D.

Data format specification: BKG_2D

Parameters:

energy_lo, energy_hi : Quantity

Energy binning

offset_lo, offset_hi : Quantity

FOV coordinate offset-axis binning

data : Quantity

Background rate (usually: s^-1 MeV^-1 sr^-1)

Attributes Summary

default_interp_kwargs

Default Interpolation kwargs for NDDataArray.

Methods Summary

evaluate(fov_lon, fov_lat, energy_reco[, method])	Evaluate at a given FOV position and energy.
from_hdulist(hdulist[, hdu])	Create from HDUList.
from_table(table)	Read from Table.
integrate_on_energy_range(fov_lon, fov_lat, …)	Integrate over an energy range.
peek()
plot(**kwargs)
read(filename[, hdu])	Read from file.
to_3d()	Convert to Background3D.
to_fits([name])	Convert to BinTableHDU.
to_table()	Convert to Table.

Attributes Documentation

default_interp_kwargs = {'bounds_error': False, 'fill_value': None}

Default Interpolation kwargs for NDDataArray. Extrapolate.

Methods Documentation

evaluate(fov_lon, fov_lat, energy_reco, method='linear', **kwargs)

Evaluate at a given FOV position and energy. The fov_lon, fov_lat, energy_reco has to have the same shape since this is a set of points on which you want to evaluate

To have the same API than background 3D for the background evaluation, the offset is fov_altaz_lon.

Parameters:

fov_lon, fov_lat : Angle

FOV coordinates expecting in AltAz frame, same shape than energy_reco

energy_reco : Quantity

Reconstructed energy, same dimension than fov_lat and fov_lat

method : str {‘linear’, ‘nearest’}, optional

Interpolation method

kwargs : dict

option for interpolation for RegularGridInterpolator

Returns:

array : Quantity

Interpolated values, axis order is the same as for the NDData array

classmethod from_hdulist(hdulist, hdu='BACKGROUND')

Create from HDUList.

classmethod from_table(table)

Read from Table.

integrate_on_energy_range(fov_lon, fov_lat, energy_range, n_integration_bins=1, method='linear', **kwargs)

Integrate over an energy range.

Parameters:

fov_lon, fov_lat : Angle

FOV coordinates expecting in AltAz frame.

energy_range: `~astropy.units.Quantity`

Energy range

n_integration_bins : int

Number of bins in the energy range

method : {‘linear’, ‘nearest’}, optional

Interpolation method

kwargs : dict

Passed to scipy.interpolate.RegularGridInterpolator.

Returns:

array : Quantity

Returns 2D array with axes offset

peek()

plot(**kwargs)

classmethod read(filename, hdu='BACKGROUND')

Read from file.

to_3d()

Convert to Background3D.

Fill in a radially symmetric way.

to_fits(name='BACKGROUND')

Convert to BinTableHDU.

to_table()

Convert to Table.